{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean radius</th>\n",
       "      <th>mean texture</th>\n",
       "      <th>mean perimeter</th>\n",
       "      <th>mean area</th>\n",
       "      <th>mean smoothness</th>\n",
       "      <th>mean compactness</th>\n",
       "      <th>mean concavity</th>\n",
       "      <th>mean concave points</th>\n",
       "      <th>mean symmetry</th>\n",
       "      <th>mean fractal dimension</th>\n",
       "      <th>...</th>\n",
       "      <th>worst radius</th>\n",
       "      <th>worst texture</th>\n",
       "      <th>worst perimeter</th>\n",
       "      <th>worst area</th>\n",
       "      <th>worst smoothness</th>\n",
       "      <th>worst compactness</th>\n",
       "      <th>worst concavity</th>\n",
       "      <th>worst concave points</th>\n",
       "      <th>worst symmetry</th>\n",
       "      <th>worst fractal dimension</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.99</td>\n",
       "      <td>10.38</td>\n",
       "      <td>122.80</td>\n",
       "      <td>1001.0</td>\n",
       "      <td>0.11840</td>\n",
       "      <td>0.27760</td>\n",
       "      <td>0.3001</td>\n",
       "      <td>0.14710</td>\n",
       "      <td>0.2419</td>\n",
       "      <td>0.07871</td>\n",
       "      <td>...</td>\n",
       "      <td>25.38</td>\n",
       "      <td>17.33</td>\n",
       "      <td>184.60</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>0.1622</td>\n",
       "      <td>0.6656</td>\n",
       "      <td>0.7119</td>\n",
       "      <td>0.2654</td>\n",
       "      <td>0.4601</td>\n",
       "      <td>0.11890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20.57</td>\n",
       "      <td>17.77</td>\n",
       "      <td>132.90</td>\n",
       "      <td>1326.0</td>\n",
       "      <td>0.08474</td>\n",
       "      <td>0.07864</td>\n",
       "      <td>0.0869</td>\n",
       "      <td>0.07017</td>\n",
       "      <td>0.1812</td>\n",
       "      <td>0.05667</td>\n",
       "      <td>...</td>\n",
       "      <td>24.99</td>\n",
       "      <td>23.41</td>\n",
       "      <td>158.80</td>\n",
       "      <td>1956.0</td>\n",
       "      <td>0.1238</td>\n",
       "      <td>0.1866</td>\n",
       "      <td>0.2416</td>\n",
       "      <td>0.1860</td>\n",
       "      <td>0.2750</td>\n",
       "      <td>0.08902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.69</td>\n",
       "      <td>21.25</td>\n",
       "      <td>130.00</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>0.10960</td>\n",
       "      <td>0.15990</td>\n",
       "      <td>0.1974</td>\n",
       "      <td>0.12790</td>\n",
       "      <td>0.2069</td>\n",
       "      <td>0.05999</td>\n",
       "      <td>...</td>\n",
       "      <td>23.57</td>\n",
       "      <td>25.53</td>\n",
       "      <td>152.50</td>\n",
       "      <td>1709.0</td>\n",
       "      <td>0.1444</td>\n",
       "      <td>0.4245</td>\n",
       "      <td>0.4504</td>\n",
       "      <td>0.2430</td>\n",
       "      <td>0.3613</td>\n",
       "      <td>0.08758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.42</td>\n",
       "      <td>20.38</td>\n",
       "      <td>77.58</td>\n",
       "      <td>386.1</td>\n",
       "      <td>0.14250</td>\n",
       "      <td>0.28390</td>\n",
       "      <td>0.2414</td>\n",
       "      <td>0.10520</td>\n",
       "      <td>0.2597</td>\n",
       "      <td>0.09744</td>\n",
       "      <td>...</td>\n",
       "      <td>14.91</td>\n",
       "      <td>26.50</td>\n",
       "      <td>98.87</td>\n",
       "      <td>567.7</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.8663</td>\n",
       "      <td>0.6869</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6638</td>\n",
       "      <td>0.17300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20.29</td>\n",
       "      <td>14.34</td>\n",
       "      <td>135.10</td>\n",
       "      <td>1297.0</td>\n",
       "      <td>0.10030</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.1980</td>\n",
       "      <td>0.10430</td>\n",
       "      <td>0.1809</td>\n",
       "      <td>0.05883</td>\n",
       "      <td>...</td>\n",
       "      <td>22.54</td>\n",
       "      <td>16.67</td>\n",
       "      <td>152.20</td>\n",
       "      <td>1575.0</td>\n",
       "      <td>0.1374</td>\n",
       "      <td>0.2050</td>\n",
       "      <td>0.4000</td>\n",
       "      <td>0.1625</td>\n",
       "      <td>0.2364</td>\n",
       "      <td>0.07678</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   mean radius  mean texture  mean perimeter  mean area  mean smoothness  \\\n",
       "0        17.99         10.38          122.80     1001.0          0.11840   \n",
       "1        20.57         17.77          132.90     1326.0          0.08474   \n",
       "2        19.69         21.25          130.00     1203.0          0.10960   \n",
       "3        11.42         20.38           77.58      386.1          0.14250   \n",
       "4        20.29         14.34          135.10     1297.0          0.10030   \n",
       "\n",
       "   mean compactness  mean concavity  mean concave points  mean symmetry  \\\n",
       "0           0.27760          0.3001              0.14710         0.2419   \n",
       "1           0.07864          0.0869              0.07017         0.1812   \n",
       "2           0.15990          0.1974              0.12790         0.2069   \n",
       "3           0.28390          0.2414              0.10520         0.2597   \n",
       "4           0.13280          0.1980              0.10430         0.1809   \n",
       "\n",
       "   mean fractal dimension  ...  worst radius  worst texture  worst perimeter  \\\n",
       "0                 0.07871  ...         25.38          17.33           184.60   \n",
       "1                 0.05667  ...         24.99          23.41           158.80   \n",
       "2                 0.05999  ...         23.57          25.53           152.50   \n",
       "3                 0.09744  ...         14.91          26.50            98.87   \n",
       "4                 0.05883  ...         22.54          16.67           152.20   \n",
       "\n",
       "   worst area  worst smoothness  worst compactness  worst concavity  \\\n",
       "0      2019.0            0.1622             0.6656           0.7119   \n",
       "1      1956.0            0.1238             0.1866           0.2416   \n",
       "2      1709.0            0.1444             0.4245           0.4504   \n",
       "3       567.7            0.2098             0.8663           0.6869   \n",
       "4      1575.0            0.1374             0.2050           0.4000   \n",
       "\n",
       "   worst concave points  worst symmetry  worst fractal dimension  \n",
       "0                0.2654          0.4601                  0.11890  \n",
       "1                0.1860          0.2750                  0.08902  \n",
       "2                0.2430          0.3613                  0.08758  \n",
       "3                0.2575          0.6638                  0.17300  \n",
       "4                0.1625          0.2364                  0.07678  \n",
       "\n",
       "[5 rows x 30 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from BorutaShap import BorutaShap, load_data\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from xgboost import XGBClassifier\n",
    "\n",
    "X, y = load_data(data_type='classification')\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████| 100/100 [00:51<00:00,  1.94it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19 attributes confirmed important: ['worst concavity', 'concave points error', 'mean radius', 'area error', 'radius error', 'worst radius', 'worst concave points', 'worst perimeter', 'worst texture', 'worst area', 'worst compactness', 'mean concavity', 'perimeter error', 'mean texture', 'mean concave points', 'mean area', 'mean compactness', 'concavity error', 'mean perimeter']\n",
      "8 attributes confirmed unimportant: ['symmetry error', 'worst symmetry', 'texture error', 'smoothness error', 'fractal dimension error', 'mean symmetry', 'mean smoothness', 'mean fractal dimension']\n",
      "3 tentative attributes remains: ['worst smoothness', 'compactness error', 'worst fractal dimension']\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "model = RandomForestClassifier(class_weight = 'balanced')\n",
    "\n",
    "# no model selected default is Random Forest, if classification is False it is a Regression problem\n",
    "Feature_Selector = BorutaShap(model=model,\n",
    "                              importance_measure='shap',\n",
    "                              classification=True)\n",
    "\n",
    "Feature_Selector.fit(X=X, y=y, n_trials=100, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Returns Boxplot of features\n",
    "Feature_Selector.plot(X_size=12, figsize=(12,8),\n",
    "            y_scale='log', which_features='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████| 100/100 [00:17<00:00,  5.84it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11 attributes confirmed important: ['worst concavity', 'worst radius', 'area error', 'worst concave points', 'worst perimeter', 'worst smoothness', 'mean texture', 'compactness error', 'worst texture', 'mean concave points', 'worst area']\n",
      "19 attributes confirmed unimportant: ['concave points error', 'worst symmetry', 'texture error', 'mean radius', 'radius error', 'mean smoothness', 'mean fractal dimension', 'worst compactness', 'symmetry error', 'mean concavity', 'perimeter error', 'worst fractal dimension', 'fractal dimension error', 'mean symmetry', 'mean area', 'mean compactness', 'concavity error', 'smoothness error', 'mean perimeter']\n",
      "0 tentative attributes remains: []\n"
     ]
    }
   ],
   "source": [
    "# The scale pos weight factor should be equal to the scale_pos_weight = count(negative examples)/count(Positive examples)\n",
    "# in this case as the classes are already equal we get one\n",
    "model = XGBClassifier()\n",
    "\n",
    "# no model selected default is Random Forest, if classification is False it is a Regression problem\n",
    "Feature_Selector = BorutaShap(model=model,\n",
    "                              importance_measure='shap',\n",
    "                              classification=True)\n",
    "\n",
    "Feature_Selector.fit(X=X, y=y, n_trials=100, random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Returns Boxplot of features\n",
    "Feature_Selector.plot(X_size=12, figsize=(12,8),\n",
    "            y_scale='log', which_features='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.6 64-bit ('borutatest': conda)",
   "language": "python",
   "name": "python37664bitborutatestcondaeccbb2ba2d924cbf80a10c62689910e2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
